Quantifying the Consequences of Missing School: Linking School Nurses to Student Absences to Standardized Achievement

Autor/in	Gottfried, Michael A.
Titel	Quantifying the Consequences of Missing School: Linking School Nurses to Student Absences to Standardized Achievement
Quelle	In: Teachers College Record, 115 (2013) 6, (30 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1467-9620
Schlagwörter	Attendance Patterns; Standardized Tests; Reading Achievement; Mathematics Achievement; Urban Schools; Elementary School Students; Observation; Student Records; Neighborhoods; Quasiexperimental Design; Data Analysis; Student Characteristics; Teacher Characteristics; Educational Environment; Gender Differences; Racial Differences; Student Behavior; Poverty; Class Size; Budgets; Correlation; English Language Learners; Special Education; Pennsylvania + Suchen Sie Ihr Suchwort? Standadised tests; Standardisierter Test; Leseleistung; Mathmatics sikills; Mathmatics achievement; Mathematical ability; Mathematische Kompetenz; Urban area; Urban areas; School; Schools; Stadtregion; Stadt; Schule; Beobachtung; Schülerakte; Neighbourhoods; Nachbarschaft; Auswertung; Lernumgebung; Pädagogische Umwelt; Schulumwelt; Geschlechterkonflikt; Rassenunterschied; Student behaviour; Schülerverhalten; Armut; Klassengröße; Finanzhaushalt; Korrelation; Special needs education; Sonderpädagogik; Sonderschulwesen
Abstract	Background/Context: Parents, policymakers, and researchers uphold that missing school has negative implications on schooling success, particularly for students in urban schools. However, it has thus far been an empirical challenge within educational research to estimate the true effect that absences have on achievement outcomes. This study addresses this issue by applying multiple quasi-experimental methods and, subsequently, contributes a more accurate understanding of the pervasive, negative effects of missing school. Purpose/Objective/Research Question/Focus of the Study: The purpose of this study is to determine the effects of individual-level absences on individual-level standardized testing achievement (reading and math) in an urban school district. Population/Participants/Subjects: The dataset compiled for this study is multilevel and longitudinal and is comprised of five elementary school cohorts within the School District of Philadelphia, for a total of N = 20,932 student observations over three academic years. Individual student records were linked to teacher, classroom, and school administrative data as well as to census residential-block neighborhood information. Research Design: This study combines secondary data analyses and quasi-experimental methods. This study begins with a baseline, linear model of achievement, where the dependent variables are Stanford Achievement Test Ninth Edition (SAT9) reading and math scores. To address issues pertaining to omitted variable bias, this study employs three methods: fixed effects, value-added, and instrumental variable models. Findings: Consistently across all methods employed in this study, the results indicate a potentially causal, detrimental negative effect of absences on both reading and math standardized achievement. The effects remain significant even after accounting for additional student, neighborhood, teacher, classroom, and school factors. Conclusions/Recommendations: This study demonstrates that after accounting for omitted variable bias in multiple capacities, the negative relationship between absences and achievement is even more detrimental than reported in previous research. With a more detailed and realistic prediction of the negative ramifications of missing school, it now becomes possible to develop data-driven educational policy. (As Provided).
Anmerkungen	Teachers College, Columbia University. P.O. Box 103, 525 West 120th Street, New York, NY 10027. Tel: 212-678-3774; Fax: 212-678-6619; e-mail: tcr@tc.edu; Web site: http://www.tcrecord.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10